knitr::opts_chunk$set(echo = FALSE,cache = TRUE)
library(xlsx)
library(ggplot2)
## Registered S3 methods overwritten by 'ggplot2':
##   method         from 
##   [.quosures     rlang
##   c.quosures     rlang
##   print.quosures rlang
library(gplots)
## 
## Attaching package: 'gplots'
## The following object is masked from 'package:stats':
## 
##     lowess
library(gridExtra)
library(corrplot)
## corrplot 0.84 loaded
library(dplyr)
## 
## Attaching package: 'dplyr'
## The following object is masked from 'package:gridExtra':
## 
##     combine
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
library(png)
library(grid)
library(heatmaply)
## Loading required package: plotly
## 
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
## 
##     last_plot
## The following object is masked from 'package:stats':
## 
##     filter
## The following object is masked from 'package:graphics':
## 
##     layout
## Loading required package: viridis
## Loading required package: viridisLite
## Registered S3 method overwritten by 'seriation':
##   method         from 
##   reorder.hclust gclus
## 
## ======================
## Welcome to heatmaply version 0.16.0
## 
## Type citation('heatmaply') for how to cite the package.
## Type ?heatmaply for the main documentation.
## 
## The github page is: https://github.com/talgalili/heatmaply/
## Please submit your suggestions and bug-reports at: https://github.com/talgalili/heatmaply/issues
## Or contact: <tal.galili@gmail.com>
## ======================
## Warning: NAs introduced by coercion
##      Tree.ID Allocation Column Row Rep. measure Height Flower Flower.Level
## 840    IN4E4         F1      2  20    N       7      M      N            0
## 1363   IN4FM         F1      3  17    N      11      H      N            0
##         Chl  Flav  Anth Height08 Height09 HD
## 840  18.511 1.401 0.370      138      234 96
## 1363 59.122 1.640 0.483      166      245 79
## Warning: Factor `Height` contains implicit NA, consider using
## `forcats::fct_explicit_na`

Tree Plots

Anthocyanin

## Warning: Removed 21 rows containing non-finite values (stat_boxplot).

## Warning: Removed 21 rows containing missing values (geom_point).

## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## Warning: Removed 21 rows containing non-finite values (stat_bin).
## Warning: Removed 21 rows containing non-finite values (stat_density).

Chlorophyll

## Warning: Removed 21 rows containing non-finite values (stat_boxplot).

## Warning: Removed 21 rows containing missing values (geom_point).

## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## Warning: Removed 21 rows containing non-finite values (stat_bin).
## Warning: Removed 21 rows containing non-finite values (stat_density).

Flavonol

## Warning: Removed 21 rows containing non-finite values (stat_boxplot).

## Warning: Removed 21 rows containing missing values (geom_point).

## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## Warning: Removed 21 rows containing non-finite values (stat_bin).
## Warning: Removed 21 rows containing non-finite values (stat_density).

Height 2018

## Warning: Removed 89 rows containing non-finite values (stat_boxplot).

## Warning: Removed 8 rows containing missing values (geom_point).

## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## Warning: Removed 8 rows containing non-finite values (stat_bin).
## Warning: Removed 8 rows containing non-finite values (stat_density).

Height 2019

## Warning: Removed 90 rows containing non-finite values (stat_boxplot).

## Warning: Removed 9 rows containing missing values (geom_point).

## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## Warning: Removed 9 rows containing non-finite values (stat_bin).
## Warning: Removed 9 rows containing non-finite values (stat_density).

Height Difference 2018-2019

## Warning: Removed 1811 rows containing non-finite values (stat_boxplot).

## Warning: Removed 180 rows containing missing values (geom_point).

## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## Warning: Removed 180 rows containing non-finite values (stat_bin).
## Warning: Removed 180 rows containing non-finite values (stat_density).

Leaf Height Plots

## Warning: Factor `Height` contains implicit NA, consider using
## `forcats::fct_explicit_na`

## Warning: Factor `Height` contains implicit NA, consider using
## `forcats::fct_explicit_na`

## Warning: Factor `Height` contains implicit NA, consider using
## `forcats::fct_explicit_na`

## Warning: Factor `Height` contains implicit NA, consider using
## `forcats::fct_explicit_na`

Anthocyanin

## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).
## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).
## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).

  • ANOVA Anthocyanin and Collection Height
## Analysis of Variance Table
## 
## Response: F1$Anth5
##             Df Sum Sq   Mean Sq F value Pr(>F)
## F1$Height    2 0.0000 1.650e-06   0.001  0.999
## Residuals 1787 3.0326 1.697e-03

## 
## Call:
## lm(formula = F1$Anth5 ~ F1$Height)
## 
## Residuals:
##       Min        1Q    Median        3Q       Max 
## -0.108092 -0.027610 -0.000777  0.025741  0.198752 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)
## (Intercept) -6.737e-05  1.846e-03  -0.036    0.971
## F1$HeightL   8.195e-05  2.452e-03   0.033    0.973
## F1$HeightM   1.049e-04  2.461e-03   0.043    0.966
## 
## Residual standard error: 0.04119 on 1787 degrees of freedom
##   (21 observations deleted due to missingness)
## Multiple R-squared:  1.089e-06,  Adjusted R-squared:  -0.001118 
## F-statistic: 0.000973 on 2 and 1787 DF,  p-value: 0.999
##                    2.5 %      97.5 %
## (Intercept) -0.003687902 0.003553152
## F1$HeightL  -0.004728010 0.004891906
## F1$HeightM  -0.004721273 0.004931111
  • R.squared Collection Height
## [1] 1.08897e-06
  • Spearman Comparing Height Levels
## Warning in cor.test.default(HM$Anth, HH$Anth, method = "spearman"): Cannot
## compute exact p-value with ties
## 
##  Spearman's rank correlation rho
## 
## data:  HM$Anth and HH$Anth
## S = 701463, p-value = 0.5556
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
##         rho 
## -0.04708476
## Warning in cor.test.default(HH$Anth, HL$Anth, method = "spearman"): Cannot
## compute exact p-value with ties
## 
##  Spearman's rank correlation rho
## 
## data:  HH$Anth and HL$Anth
## S = 725230, p-value = 0.3008
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
##         rho 
## -0.08256216
## 
##  Spearman's rank correlation rho
## 
## data:  HM$Anth and HL$Anth
## S = 691294, p-value = 0.6894
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
##        rho 
## -0.0319053

Chlorophyll

## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).
## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).
## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).

  • ANOVA Chlorophyll and Collection Height
## Analysis of Variance Table
## 
## Response: F1$Chl5
##             Df Sum Sq Mean Sq F value Pr(>F)
## F1$Height    2    802  401.03  1.8488 0.1577
## Residuals 1787 387632  216.92

##                   2.5 %    97.5 %
## (Intercept) -2.34392260 0.2449164
## F1$HeightL  -0.08648552 3.3528501
## F1$HeightM  -0.45338321 2.9975606
  • R.squared Collection Height
## [1] 0.002064874
  • Spearman Comparing Height Levels
## 
##  Spearman's rank correlation rho
## 
## data:  HM$Chl and HH$Chl
## S = 780026, p-value = 0.03853
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
##        rho 
## -0.1643569
## 
##  Spearman's rank correlation rho
## 
## data:  HH$Chl and HL$Chl
## S = 793142, p-value = 0.02041
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
##        rho 
## -0.1839354
## 
##  Spearman's rank correlation rho
## 
## data:  HM$Chl and HL$Chl
## S = 731494, p-value = 0.2489
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
##         rho 
## -0.09191247

Flavonol

## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).
## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).
## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).

  • ANOVA Flavonol and Collection Height
## Analysis of Variance Table
## 
## Response: F1$Flav5
##             Df Sum Sq  Mean Sq F value Pr(>F)
## F1$Height    2  0.001 0.000562  0.0102 0.9899
## Residuals 1787 98.658 0.055209

##                   2.5 %     97.5 %
## (Intercept) -0.02186947 0.01943162
## F1$HeightL  -0.02547173 0.02939778
## F1$HeightM  -0.02611714 0.02893756
  • R.squared Collection Height
## [1] 1.139096e-05
  • Spearman Comparing Height Levels
## 
##  Spearman's rank correlation rho
## 
## data:  HM$Flav and HH$Flav
## S = 578494, p-value = 0.08629
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
##      rho 
## 0.136473
## 
##  Spearman's rank correlation rho
## 
## data:  HH$Flav and HL$Flav
## S = 619624, p-value = 0.3466
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
##        rho 
## 0.07507762
## 
##  Spearman's rank correlation rho
## 
## data:  HM$Flav and HL$Flav
## S = 520262, p-value = 0.004727
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
##       rho 
## 0.2233968

Row Plots

Anthocyanin

## Warning: Removed 21 rows containing non-finite values (stat_boxplot).

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Anth5
##             Df  Sum Sq    Mean Sq F value Pr(>F)
## F1$Row      49 0.00009 0.00000191  0.0011      1
## Residuals 1740 3.03249 0.00174281

## 
## Call:
## lm(formula = F1$Anth5 ~ F1$Row)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.10823 -0.02772 -0.00075  0.02580  0.19883 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.236e-04  6.026e-03  -0.021    0.984
## F1$Row10    -4.004e-04  9.527e-03  -0.042    0.966
## F1$Row11     1.971e-06  8.478e-03   0.000    1.000
## F1$Row12     2.002e-04  9.527e-03   0.021    0.983
## F1$Row13     6.312e-05  9.819e-03   0.006    0.995
## F1$Row14     1.970e-04  9.440e-03   0.021    0.983
## F1$Row15     1.970e-04  9.440e-03   0.021    0.983
## F1$Row16     1.123e-05  9.716e-03   0.001    0.999
## F1$Row17     5.573e-04  1.092e-02   0.051    0.959
## F1$Row18     1.123e-05  9.716e-03   0.001    0.999
## F1$Row19     1.970e-04  9.440e-03   0.021    0.983
## F1$Row2      1.970e-04  9.440e-03   0.021    0.983
## F1$Row20     6.273e-05  8.766e-03   0.007    0.994
## F1$Row21     1.432e-04  9.133e-03   0.016    0.987
## F1$Row22     1.970e-04  9.440e-03   0.021    0.983
## F1$Row23     6.273e-05  8.766e-03   0.007    0.994
## F1$Row24     6.013e-04  9.440e-03   0.064    0.949
## F1$Row25     1.970e-04  9.440e-03   0.021    0.983
## F1$Row26     6.852e-04  9.619e-03   0.071    0.943
## F1$Row27     4.335e-04  9.527e-03   0.045    0.964
## F1$Row28     1.970e-04  9.440e-03   0.021    0.983
## F1$Row29    -4.004e-04  9.527e-03  -0.042    0.966
## F1$Row3      1.970e-04  9.440e-03   0.021    0.983
## F1$Row30    -1.846e-04  9.716e-03  -0.019    0.985
## F1$Row31    -4.212e-04  8.766e-03  -0.048    0.962
## F1$Row32     1.970e-04  8.713e-03   0.023    0.982
## F1$Row33     1.970e-04  9.440e-03   0.021    0.983
## F1$Row34     1.970e-04  8.713e-03   0.023    0.982
## F1$Row35     2.890e-05  8.662e-03   0.003    0.997
## F1$Row36     2.002e-04  9.527e-03   0.021    0.983
## F1$Row37     2.002e-04  9.527e-03   0.021    0.983
## F1$Row38    -1.756e-04  9.619e-03  -0.018    0.985
## F1$Row39     1.970e-04  9.440e-03   0.021    0.983
## F1$Row4     -2.072e-04  9.440e-03  -0.022    0.982
## F1$Row40     1.970e-04  9.440e-03   0.021    0.983
## F1$Row41     3.156e-04  8.567e-03   0.037    0.971
## F1$Row42     3.751e-04  9.440e-03   0.040    0.968
## F1$Row43     2.548e-04  9.619e-03   0.026    0.979
## F1$Row44     4.335e-04  9.527e-03   0.045    0.964
## F1$Row45     6.273e-05  8.766e-03   0.007    0.994
## F1$Row46     5.096e-04  8.766e-03   0.058    0.954
## F1$Row47    -1.109e-04  8.766e-03  -0.013    0.990
## F1$Row48     1.899e-05  9.440e-03   0.002    0.998
## F1$Row49     1.970e-04  8.713e-03   0.023    0.982
## F1$Row5      2.002e-04  9.527e-03   0.021    0.983
## F1$Row50    -1.715e-04  8.178e-03  -0.021    0.983
## F1$Row6      1.970e-04  9.440e-03   0.021    0.983
## F1$Row7      1.970e-04  9.440e-03   0.021    0.983
## F1$Row8      1.970e-04  9.440e-03   0.021    0.983
## F1$Row9     -2.550e-05  9.358e-03  -0.003    0.998
## 
## Residual standard error: 0.04175 on 1740 degrees of freedom
##   (21 observations deleted due to missingness)
## Multiple R-squared:  3.078e-05,  Adjusted R-squared:  -0.02813 
## F-statistic: 0.001093 on 49 and 1740 DF,  p-value: 1
## [1] -9.57882e-18
##                   2.5 %     97.5 %
## (Intercept) -0.01194186 0.01169474
## F1$Row10    -0.01908672 0.01828602
## F1$Row11    -0.01662614 0.01663008
## F1$Row12    -0.01848620 0.01888655
## F1$Row13    -0.01919444 0.01932068
## F1$Row14    -0.01831868 0.01871275
## F1$Row15    -0.01831868 0.01871275
## F1$Row16    -0.01904520 0.01906766
## F1$Row17    -0.02086516 0.02197981
## F1$Row18    -0.01904520 0.01906766
## F1$Row19    -0.01831868 0.01871275
## F1$Row2     -0.01831868 0.01871275
## F1$Row20    -0.01712986 0.01725533
## F1$Row21    -0.01776961 0.01805600
## F1$Row22    -0.01831868 0.01871275
## F1$Row23    -0.01712986 0.01725533
## F1$Row24    -0.01791440 0.01911703
## F1$Row25    -0.01831868 0.01871275
## F1$Row26    -0.01818116 0.01955152
## F1$Row27    -0.01825289 0.01911985
## F1$Row28    -0.01831868 0.01871275
## F1$Row29    -0.01908672 0.01828602
## F1$Row3     -0.01831868 0.01871275
## F1$Row30    -0.01924106 0.01887181
## F1$Row31    -0.01761375 0.01677144
## F1$Row32    -0.01689220 0.01728627
## F1$Row33    -0.01831868 0.01871275
## F1$Row34    -0.01689220 0.01728627
## F1$Row35    -0.01696098 0.01701877
## F1$Row36    -0.01848620 0.01888655
## F1$Row37    -0.01848620 0.01888655
## F1$Row38    -0.01904189 0.01869079
## F1$Row39    -0.01831868 0.01871275
## F1$Row4     -0.01872296 0.01830847
## F1$Row40    -0.01831868 0.01871275
## F1$Row41    -0.01648663 0.01711790
## F1$Row42    -0.01814063 0.01889080
## F1$Row43    -0.01861153 0.01912115
## F1$Row44    -0.01825289 0.01911985
## F1$Row45    -0.01712986 0.01725533
## F1$Row46    -0.01668296 0.01770223
## F1$Row47    -0.01730348 0.01708171
## F1$Row48    -0.01849673 0.01853470
## F1$Row49    -0.01689220 0.01728627
## F1$Row5     -0.01848620 0.01888655
## F1$Row50    -0.01621181 0.01586877
## F1$Row6     -0.01831868 0.01871275
## F1$Row7     -0.01831868 0.01871275
## F1$Row8     -0.01831868 0.01871275
## F1$Row9     -0.01837915 0.01832815
  • R.squared
## [1] 3.078204e-05

Chlorophyll

## Warning: Removed 21 rows containing non-finite values (stat_boxplot).

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Chl5
##             Df Sum Sq Mean Sq F value Pr(>F)
## F1$Row      49      0    0.00       0      1
## Residuals 1740 388434  223.24

## 
## Call:
## lm(formula = F1$Chl5 ~ F1$Row)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -40.413 -10.889   1.258  11.488  30.448 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)
## (Intercept)  5.122e-14  2.157e+00       0        1
## F1$Row10    -5.443e-14  3.410e+00       0        1
## F1$Row11    -5.868e-14  3.034e+00       0        1
## F1$Row12    -4.608e-14  3.410e+00       0        1
## F1$Row13    -4.346e-14  3.514e+00       0        1
## F1$Row14    -4.472e-14  3.379e+00       0        1
## F1$Row15    -5.143e-14  3.379e+00       0        1
## F1$Row16    -4.709e-14  3.477e+00       0        1
## F1$Row17    -2.396e-14  3.909e+00       0        1
## F1$Row18    -4.307e-14  3.477e+00       0        1
## F1$Row19    -8.068e-14  3.379e+00       0        1
## F1$Row2     -3.876e-14  3.379e+00       0        1
## F1$Row20    -5.483e-14  3.137e+00       0        1
## F1$Row21    -5.324e-14  3.269e+00       0        1
## F1$Row22    -5.665e-14  3.379e+00       0        1
## F1$Row23    -5.097e-14  3.137e+00       0        1
## F1$Row24    -3.762e-14  3.379e+00       0        1
## F1$Row25    -4.563e-14  3.379e+00       0        1
## F1$Row26    -5.032e-14  3.443e+00       0        1
## F1$Row27    -5.458e-14  3.410e+00       0        1
## F1$Row28    -4.724e-14  3.379e+00       0        1
## F1$Row29    -3.408e-14  3.410e+00       0        1
## F1$Row3     -4.192e-14  3.379e+00       0        1
## F1$Row30    -5.594e-14  3.477e+00       0        1
## F1$Row31     1.341e-14  3.137e+00       0        1
## F1$Row32    -5.711e-14  3.118e+00       0        1
## F1$Row33    -5.905e-14  3.379e+00       0        1
## F1$Row34    -5.094e-14  3.118e+00       0        1
## F1$Row35    -6.647e-14  3.100e+00       0        1
## F1$Row36    -5.311e-14  3.410e+00       0        1
## F1$Row37    -9.871e-15  3.410e+00       0        1
## F1$Row38    -4.983e-14  3.443e+00       0        1
## F1$Row39    -5.183e-14  3.379e+00       0        1
## F1$Row4     -5.165e-14  3.379e+00       0        1
## F1$Row40    -6.223e-14  3.379e+00       0        1
## F1$Row41    -5.581e-14  3.066e+00       0        1
## F1$Row42    -5.669e-14  3.379e+00       0        1
## F1$Row43    -5.319e-14  3.443e+00       0        1
## F1$Row44    -7.369e-14  3.410e+00       0        1
## F1$Row45    -6.561e-14  3.137e+00       0        1
## F1$Row46    -8.051e-14  3.137e+00       0        1
## F1$Row47    -6.965e-14  3.137e+00       0        1
## F1$Row48    -6.373e-14  3.379e+00       0        1
## F1$Row49    -4.888e-14  3.118e+00       0        1
## F1$Row5     -6.082e-14  3.410e+00       0        1
## F1$Row50    -6.229e-14  2.927e+00       0        1
## F1$Row6     -4.716e-14  3.379e+00       0        1
## F1$Row7     -6.638e-14  3.379e+00       0        1
## F1$Row8     -6.942e-14  3.379e+00       0        1
## F1$Row9     -7.645e-14  3.349e+00       0        1
## 
## Residual standard error: 14.94 on 1740 degrees of freedom
##   (21 observations deleted due to missingness)
## Multiple R-squared:  1.668e-29,  Adjusted R-squared:  -0.02816 
## F-statistic: 5.924e-28 on 49 and 1740 DF,  p-value: 1
  • R.squared
## [1] 1.668271e-29

Flavonol

## Warning: Removed 21 rows containing non-finite values (stat_boxplot).

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Flav5
##             Df Sum Sq  Mean Sq F value Pr(>F)
## F1$Row      49  0.200 0.004090  0.0723      1
## Residuals 1740 98.459 0.056585

## 
## Call:
## lm(formula = F1$Flav5 ~ F1$Row)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.87631 -0.14319  0.01576  0.15006  0.83162 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.0160350  0.0343346  -0.467    0.641
## F1$Row10     0.0122635  0.0542877   0.226    0.821
## F1$Row11    -0.0007709  0.0483081  -0.016    0.987
## F1$Row12     0.0109164  0.0542877   0.201    0.841
## F1$Row13     0.0113525  0.0559472   0.203    0.839
## F1$Row14     0.0109282  0.0537920   0.203    0.839
## F1$Row15     0.0109282  0.0537920   0.203    0.839
## F1$Row16     0.0159958  0.0553629   0.289    0.773
## F1$Row17     0.0285742  0.0622367   0.459    0.646
## F1$Row18     0.0110881  0.0553629   0.200    0.841
## F1$Row19     0.0109282  0.0537920   0.203    0.839
## F1$Row2      0.0109282  0.0537920   0.203    0.839
## F1$Row20     0.0175783  0.0499480   0.352    0.725
## F1$Row21     0.0067765  0.0520404   0.130    0.896
## F1$Row22     0.0109282  0.0537920   0.203    0.839
## F1$Row23     0.0370839  0.0499480   0.742    0.458
## F1$Row24     0.0073530  0.0537920   0.137    0.891
## F1$Row25     0.0109282  0.0537920   0.203    0.839
## F1$Row26     0.0089356  0.0548106   0.163    0.871
## F1$Row27     0.0094440  0.0542877   0.174    0.862
## F1$Row28     0.0109282  0.0537920   0.203    0.839
## F1$Row29     0.0147885  0.0542877   0.272    0.785
## F1$Row3      0.0109282  0.0537920   0.203    0.839
## F1$Row30     0.0118640  0.0553629   0.214    0.830
## F1$Row31     0.0048055  0.0499480   0.096    0.923
## F1$Row32     0.0352480  0.0496477   0.710    0.478
## F1$Row33     0.0109282  0.0537920   0.203    0.839
## F1$Row34     0.0352480  0.0496477   0.710    0.478
## F1$Row35     0.0346724  0.0493591   0.702    0.482
## F1$Row36     0.0124501  0.0542877   0.229    0.819
## F1$Row37     0.0124501  0.0542877   0.229    0.819
## F1$Row38     0.0128693  0.0548106   0.235    0.814
## F1$Row39     0.0109282  0.0537920   0.203    0.839
## F1$Row4      0.0125355  0.0537920   0.233    0.816
## F1$Row40     0.0109282  0.0537920   0.203    0.839
## F1$Row41     0.0218259  0.0488140   0.447    0.655
## F1$Row42     0.0107487  0.0537920   0.200    0.842
## F1$Row43     0.0095752  0.0548106   0.175    0.861
## F1$Row44     0.0109777  0.0542877   0.202    0.840
## F1$Row45     0.0359426  0.0499480   0.720    0.472
## F1$Row46     0.0357126  0.0499480   0.715    0.475
## F1$Row47     0.0350335  0.0499480   0.701    0.483
## F1$Row48     0.0106271  0.0537920   0.198    0.843
## F1$Row49     0.0352480  0.0496477   0.710    0.478
## F1$Row5      0.0124501  0.0542877   0.229    0.819
## F1$Row50     0.0200420  0.0466003   0.430    0.667
## F1$Row6      0.0109282  0.0537920   0.203    0.839
## F1$Row7      0.0109282  0.0537920   0.203    0.839
## F1$Row8      0.0109282  0.0537920   0.203    0.839
## F1$Row9      0.0123251  0.0533211   0.231    0.817
## 
## Residual standard error: 0.2379 on 1740 degrees of freedom
##   (21 observations deleted due to missingness)
## Multiple R-squared:  0.002032,   Adjusted R-squared:  -0.02607 
## F-statistic: 0.07229 on 49 and 1740 DF,  p-value: 1
  • R.squared
## [1] 0.002031552

Height 2018

## Warning: Removed 89 rows containing non-finite values (stat_boxplot).

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$H185
##             Df Sum Sq Mean Sq F value    Pr(>F)    
## F1$Row      49  24288  495.68  2.1009 1.659e-05 ***
## Residuals 1672 394486  235.94                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

## 
## Call:
## lm(formula = F1$H185 ~ F1$Row)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -52.933 -11.518  -0.736  11.531  39.018 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   8.5699     2.5252   3.394 0.000706 ***
## F1$Row10     -7.3312     3.7081  -1.977 0.048195 *  
## F1$Row11     -4.5365     3.3454  -1.356 0.175273    
## F1$Row12     -6.7638     3.7081  -1.824 0.068317 .  
## F1$Row13     -6.0953     3.8095  -1.600 0.109780    
## F1$Row14     -7.1737     3.6778  -1.951 0.051279 .  
## F1$Row15     -0.6156     4.1353  -0.149 0.881685    
## F1$Row16     -7.9814     3.7738  -2.115 0.034581 *  
## F1$Row17    -10.2487     4.1353  -2.478 0.013299 *  
## F1$Row18     -5.8621     3.7738  -1.553 0.120521    
## F1$Row19     -7.1737     3.6778  -1.951 0.051279 .  
## F1$Row2      -7.1737     3.6778  -1.951 0.051279 .  
## F1$Row20     -6.0017     3.4444  -1.742 0.081610 .  
## F1$Row21     -7.0921     3.5476  -1.999 0.045758 *  
## F1$Row22     -8.0326     3.6491  -2.201 0.027854 *  
## F1$Row23    -14.8322     3.4444  -4.306 1.76e-05 ***
## F1$Row24     -7.9433     3.6491  -2.177 0.029636 *  
## F1$Row25     -8.0326     3.6491  -2.201 0.027854 *  
## F1$Row26     -8.4962     3.7081  -2.291 0.022071 *  
## F1$Row27    -11.9432     4.1353  -2.888 0.003926 ** 
## F1$Row28     -8.0326     3.6491  -2.201 0.027854 *  
## F1$Row29    -10.9642     4.1966  -2.613 0.009066 ** 
## F1$Row3      -7.1737     3.6778  -1.951 0.051279 .  
## F1$Row30     -8.7014     3.7400  -2.327 0.020106 *  
## F1$Row31     -6.0018     3.4262  -1.752 0.080001 .  
## F1$Row32    -14.4746     3.4262  -4.225 2.52e-05 ***
## F1$Row33     -8.0326     3.6491  -2.201 0.027854 *  
## F1$Row34    -14.4746     3.4262  -4.225 2.52e-05 ***
## F1$Row35    -14.1328     3.4088  -4.146 3.55e-05 ***
## F1$Row36     -8.3034     3.6778  -2.258 0.024093 *  
## F1$Row37     -8.3034     3.6778  -2.258 0.024093 *  
## F1$Row38     -7.9288     3.7081  -2.138 0.032640 *  
## F1$Row39     -2.1704     4.0786  -0.532 0.594691    
## F1$Row4      -0.6156     4.1353  -0.149 0.881685    
## F1$Row40     -2.1704     4.0786  -0.532 0.594691    
## F1$Row41    -11.1135     3.3759  -3.292 0.001015 ** 
## F1$Row42     -8.0326     3.6491  -2.201 0.027854 *  
## F1$Row43     -7.2665     3.7081  -1.960 0.050201 .  
## F1$Row44     -8.3034     3.6778  -2.258 0.024093 *  
## F1$Row45    -14.3393     3.4444  -4.163 3.30e-05 ***
## F1$Row46    -14.8322     3.4444  -4.306 1.76e-05 ***
## F1$Row47    -13.9652     3.4444  -4.055 5.25e-05 ***
## F1$Row48     -8.5666     3.6491  -2.348 0.019011 *  
## F1$Row49    -14.4746     3.4262  -4.225 2.52e-05 ***
## F1$Row5      -0.6879     4.1966  -0.164 0.869820    
## F1$Row50    -10.3134     3.2428  -3.180 0.001498 ** 
## F1$Row6      -7.1737     3.6778  -1.951 0.051279 .  
## F1$Row7      -7.1737     3.6778  -1.951 0.051279 .  
## F1$Row8      -7.1737     3.6778  -1.951 0.051279 .  
## F1$Row9      -7.5595     3.6491  -2.072 0.038456 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 15.36 on 1672 degrees of freedom
##   (89 observations deleted due to missingness)
## Multiple R-squared:  0.058,  Adjusted R-squared:  0.03039 
## F-statistic: 2.101 on 49 and 1672 DF,  p-value: 1.659e-05

## [1] "numeric"
## Warning in cor.test.default(F1$Anth5, F1$Row2, method = "spearman"): Cannot
## compute exact p-value with ties
## 
##  Spearman's rank correlation rho
## 
## data:  F1$Anth5 and F1$Row2
## S = 954253100, p-value = 0.9423
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
##        rho 
## 0.00171195
  • R.squared
## [1] 0.05799867

Height 2019

## Warning: Removed 90 rows containing non-finite values (stat_boxplot).
## Warning: Removed 90 rows containing non-finite values (stat_summary).

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$H195
##             Df Sum Sq Mean Sq F value    Pr(>F)    
## F1$Row      49  36836  751.76  3.2009 1.777e-12 ***
## Residuals 1671 392453  234.86                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

## 
## Call:
## lm(formula = F1$H195 ~ F1$Row)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -47.068  -9.354   1.204  10.862  38.322 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   12.495      2.519   4.959 7.79e-07 ***
## F1$Row10     -11.677      3.700  -3.156 0.001626 ** 
## F1$Row11      -7.027      3.338  -2.105 0.035411 *  
## F1$Row12     -10.852      3.700  -2.933 0.003399 ** 
## F1$Row13      -9.877      3.801  -2.599 0.009444 ** 
## F1$Row14     -11.478      3.669  -3.128 0.001791 ** 
## F1$Row15      -1.467      4.126  -0.356 0.722127    
## F1$Row16     -12.841      3.765  -3.410 0.000664 ***
## F1$Row17     -17.664      4.187  -4.219 2.59e-05 ***
## F1$Row18      -9.476      3.765  -2.517 0.011939 *  
## F1$Row19     -11.478      3.669  -3.128 0.001791 ** 
## F1$Row2      -11.478      3.669  -3.128 0.001791 ** 
## F1$Row20      -9.992      3.436  -2.908 0.003691 ** 
## F1$Row21     -10.820      3.540  -3.057 0.002272 ** 
## F1$Row22     -12.346      3.641  -3.391 0.000713 ***
## F1$Row23     -19.346      3.436  -5.629 2.12e-08 ***
## F1$Row24     -12.133      3.641  -3.333 0.000879 ***
## F1$Row25     -12.346      3.641  -3.391 0.000713 ***
## F1$Row26     -13.026      3.700  -3.521 0.000442 ***
## F1$Row27     -18.724      4.126  -4.538 6.08e-06 ***
## F1$Row28     -12.346      3.641  -3.391 0.000713 ***
## F1$Row29     -15.926      4.187  -3.804 0.000148 ***
## F1$Row3      -11.478      3.669  -3.128 0.001791 ** 
## F1$Row30     -13.282      3.731  -3.559 0.000382 ***
## F1$Row31      -9.051      3.418  -2.648 0.008180 ** 
## F1$Row32     -18.857      3.418  -5.516 4.00e-08 ***
## F1$Row33     -12.346      3.641  -3.391 0.000713 ***
## F1$Row34     -18.857      3.418  -5.516 4.00e-08 ***
## F1$Row35     -18.390      3.401  -5.407 7.32e-08 ***
## F1$Row36     -12.785      3.669  -3.484 0.000506 ***
## F1$Row37     -12.785      3.669  -3.484 0.000506 ***
## F1$Row38     -12.200      3.700  -3.298 0.000995 ***
## F1$Row39      -3.186      4.069  -0.783 0.433764    
## F1$Row4       -1.467      4.126  -0.356 0.722127    
## F1$Row40      -3.186      4.069  -0.783 0.433764    
## F1$Row41     -14.762      3.368  -4.383 1.24e-05 ***
## F1$Row42     -12.346      3.641  -3.391 0.000713 ***
## F1$Row43     -11.149      3.700  -3.014 0.002621 ** 
## F1$Row44     -12.785      3.669  -3.484 0.000506 ***
## F1$Row45     -18.563      3.436  -5.402 7.55e-08 ***
## F1$Row46     -19.346      3.436  -5.629 2.12e-08 ***
## F1$Row47     -18.342      3.436  -5.337 1.07e-07 ***
## F1$Row48     -13.123      3.641  -3.604 0.000322 ***
## F1$Row49     -18.857      3.418  -5.516 4.00e-08 ***
## F1$Row5       -1.640      4.187  -0.392 0.695367    
## F1$Row50     -13.308      3.235  -4.113 4.09e-05 ***
## F1$Row6      -11.478      3.669  -3.128 0.001791 ** 
## F1$Row7      -11.478      3.669  -3.128 0.001791 ** 
## F1$Row8      -11.478      3.669  -3.128 0.001791 ** 
## F1$Row9      -12.067      3.641  -3.314 0.000938 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 15.33 on 1671 degrees of freedom
##   (90 observations deleted due to missingness)
## Multiple R-squared:  0.08581,    Adjusted R-squared:  0.059 
## F-statistic: 3.201 on 49 and 1671 DF,  p-value: 1.777e-12
##                  2.5 %     97.5 %
## (Intercept)   7.553141  17.436343
## F1$Row10    -18.933812  -4.421146
## F1$Row11    -13.573779  -0.480487
## F1$Row12    -18.108467  -3.595800
## F1$Row13    -17.331566  -2.421807
## F1$Row14    -18.674913  -4.280640
## F1$Row15     -9.559984   6.625003
## F1$Row16    -20.225683  -5.455889
## F1$Row17    -25.876426  -9.451554
## F1$Row18    -16.860616  -2.090822
## F1$Row19    -18.674913  -4.280640
## F1$Row2     -18.674913  -4.280640
## F1$Row20    -16.731907  -3.251332
## F1$Row21    -17.762138  -3.877438
## F1$Row22    -19.486891  -5.204945
## F1$Row23    -26.085855 -12.605279
## F1$Row24    -19.273961  -4.992015
## F1$Row25    -19.486891  -5.204945
## F1$Row26    -20.282153  -5.769486
## F1$Row27    -26.816965 -10.631979
## F1$Row28    -19.486891  -5.204945
## F1$Row29    -24.138859  -7.713986
## F1$Row3     -18.674913  -4.280640
## F1$Row30    -20.600725  -5.963077
## F1$Row31    -15.755633  -2.346095
## F1$Row32    -25.561748 -12.152210
## F1$Row33    -19.486891  -5.204945
## F1$Row34    -25.561748 -12.152210
## F1$Row35    -25.060758 -11.719453
## F1$Row36    -19.982395  -5.588122
## F1$Row37    -19.982395  -5.588122
## F1$Row38    -19.456808  -4.944141
## F1$Row39    -11.167465   4.795346
## F1$Row4      -9.559984   6.625003
## F1$Row40    -11.167465   4.795346
## F1$Row41    -21.368203  -8.155601
## F1$Row42    -19.486891  -5.204945
## F1$Row43    -18.405224  -3.892558
## F1$Row44    -19.982395  -5.588122
## F1$Row45    -25.303281 -11.822706
## F1$Row46    -26.085855 -12.605279
## F1$Row47    -25.082439 -11.601863
## F1$Row48    -20.263686  -5.981741
## F1$Row49    -25.561748 -12.152210
## F1$Row5      -9.852299   6.572574
## F1$Row50    -19.654335  -6.962507
## F1$Row6     -18.674913  -4.280640
## F1$Row7     -18.674913  -4.280640
## F1$Row8     -18.674913  -4.280640
## F1$Row9     -19.207590  -4.925644

  • R.squared
## [1] 0.08580726

Height Difference 2018-2019

## Warning: Removed 90 rows containing non-finite values (stat_boxplot).

## Warning: Removed 50 rows containing missing values (geom_point).

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$HD5
##             Df Sum Sq Mean Sq F value Pr(>F)
## F1$Row      49   2380  48.577  0.2137      1
## Residuals 1671 379803 227.291

##                  2.5 %   97.5 %
## (Intercept)  -0.953871 8.768738
## F1$Row10    -11.472973 2.803876
## F1$Row11     -8.925979 3.954559
## F1$Row12    -11.215002 3.061848
## F1$Row13    -11.103379 3.564111
## F1$Row14    -11.372186 2.788193
## F1$Row15     -8.806285 7.115710
## F1$Row16    -12.110071 2.419728
## F1$Row17    -14.940314 1.217669
## F1$Row18    -10.867554 3.662245
## F1$Row19    -11.372186 2.788193
## F1$Row2     -11.372186 2.788193
## F1$Row20    -10.606094 2.655434
## F1$Row21    -10.547209 3.111877
## F1$Row22    -11.325831 2.724047
## F1$Row23    -11.128777 2.132751
## F1$Row24    -11.203181 2.846696
## F1$Row25    -11.325831 2.724047
## F1$Row26    -11.655292 2.621557
## F1$Row27    -14.719280 1.202715
## F1$Row28    -11.325831 2.724047
## F1$Row29    -13.033803 3.124181
## F1$Row3     -11.372186 2.788193
## F1$Row30    -11.767945 2.631854
## F1$Row31     -9.637477 3.554169
## F1$Row32    -10.963432 2.228214
## F1$Row33    -11.325831 2.724047
## F1$Row34    -10.963432 2.228214
## F1$Row35    -10.805262 2.319260
## F1$Row36    -11.548980 2.611399
## F1$Row37    -11.548980 2.611399
## F1$Row38    -11.397321 2.879529
## F1$Row39     -8.860010 6.843421
## F1$Row4      -8.806285 7.115710
## F1$Row40     -8.860010 6.843421
## F1$Row41    -10.136252 2.861659
## F1$Row42    -11.325831 2.724047
## F1$Row43    -11.009034 3.267815
## F1$Row44    -11.548980 2.611399
## F1$Row45    -10.839820 2.421709
## F1$Row46    -11.128777 2.132751
## F1$Row47    -10.993098 2.268430
## F1$Row48    -11.568627 2.481250
## F1$Row49    -10.963432 2.228214
## F1$Row5      -9.023567 7.134417
## F1$Row50     -9.229181 3.256416
## F1$Row6     -11.372186 2.788193
## F1$Row7     -11.372186 2.788193
## F1$Row8     -11.372186 2.788193
## F1$Row9     -11.519683 2.530195

+R.squared

## [1] 0.006228143

Column Plots

Anthocyanin

## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing non-finite values (stat_summary).

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Anth5
##             Df  Sum Sq   Mean Sq F value Pr(>F)
## F1$Column    3 0.00847 0.0028245  1.6681 0.1719
## Residuals 1786 3.02411 0.0016932

  • R.squared
## [1] 0.002794171

Chlorophyll

## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing non-finite values (stat_summary).

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Chl5
##             Df Sum Sq Mean Sq F value  Pr(>F)  
## F1$Column    3   1961  653.53  3.0201 0.02876 *
## Residuals 1786 386473  216.39                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared
## [1] 0.005047411

Flavonol

## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing non-finite values (stat_summary).

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Flav5
##             Df Sum Sq  Mean Sq F value Pr(>F)
## F1$Column    3  0.011 0.003626  0.0657 0.9781
## Residuals 1786 98.648 0.055234

  • R.squared
## [1] 0.0001102635

Height 2018

## Warning: Removed 89 rows containing non-finite values (stat_boxplot).
## Warning: Removed 89 rows containing non-finite values (stat_summary).

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$H185
##             Df Sum Sq Mean Sq F value    Pr(>F)    
## F1$Column    3  15817  5272.4  22.479 2.826e-14 ***
## Residuals 1718 402957   234.6                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared
## [1] 0.03776989

Height 2019

## Warning: Removed 90 rows containing non-finite values (stat_boxplot).
## Warning: Removed 90 rows containing non-finite values (stat_summary).

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$H195
##             Df Sum Sq Mean Sq F value    Pr(>F)    
## F1$Column    3  23664  7887.8  33.389 < 2.2e-16 ***
## Residuals 1717 405626   236.2                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared
## [1] 0.05512251

Height Difference 2018-2019

## Warning: Removed 90 rows containing non-finite values (stat_boxplot).
## Warning: Removed 90 rows containing non-finite values (stat_summary).

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$HD5
##             Df Sum Sq Mean Sq F value  Pr(>F)  
## F1$Column    3   1938  646.10  2.9175 0.03306 *
## Residuals 1717 380245  221.46                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared
## [1] 0.005071636

Flowering and Flowering Levels

Flowering refers to presence or not of flowers, Flower Level refers to a measure relating to the number of flowers present (0 = no flowers, 1 = 1-10, 2 = 10-20, 3 = 20+)

Anthocyanin

## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing non-finite values (stat_summary).

  • ANOVA Flowering Level
## Analysis of Variance Table
## 
## Response: F1$Anth5
##                   Df  Sum Sq   Mean Sq F value Pr(>F)
## F1$Flower.Level    3 0.00336 0.0011185  0.6595  0.577
## Residuals       1786 3.02923 0.0016961

  • R.squared Flowering Level
## [1] 0.001106519
  • T.tests comparing Flowering Levels and Anthocyanin
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$Anth and FLWR1$Anth
## t = 0.10961, df = 17.641, p-value = 0.914
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.007844330  0.008706595
## sample estimates:
##     mean of x     mean of y 
## -4.216424e-05 -4.732968e-04
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$Anth and FLWR2$Anth
## t = 0.48384, df = 9.6247, p-value = 0.6393
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.006494169  0.010072631
## sample estimates:
##     mean of x     mean of y 
## -4.216424e-05 -1.831395e-03
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$Anth and FLWR3$Anth
## t = -1.1413, df = 10.155, p-value = 0.28
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.015283754  0.004915834
## sample estimates:
##     mean of x     mean of y 
## -4.216424e-05  5.141795e-03
## 
##  Welch Two Sample t-test
## 
## data:  FLWR1$Anth and FLWR2$Anth
## t = 0.26272, df = 21.657, p-value = 0.7953
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.009372419  0.012088616
## sample estimates:
##     mean of x     mean of y 
## -0.0004732968 -0.0018313954
## 
##  Welch Two Sample t-test
## 
## data:  FLWR1$Anth and FLWR3$Anth
## t = -0.96756, df = 20.452, p-value = 0.3446
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.017703586  0.006473401
## sample estimates:
##     mean of x     mean of y 
## -0.0004732968  0.0051417955
## 
##  Welch Two Sample t-test
## 
## data:  FLWR2$Anth and FLWR3$Anth
## t = -1.2349, df = 16.578, p-value = 0.2341
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.018909645  0.004963264
## sample estimates:
##    mean of x    mean of y 
## -0.001831395  0.005141795
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing non-finite values (stat_summary).

  • ANOVA Flowering Presence
## Analysis of Variance Table
## 
## Response: F1$Anth5
##             Df  Sum Sq    Mean Sq F value Pr(>F)
## F1$Flower    1 0.00014 0.00014274  0.0842 0.7718
## Residuals 1788 3.03244 0.00169600

  • R.squared Flowering Presence
## [1] 4.70678e-05

Chlorophyll

## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing non-finite values (stat_summary).

  • ANOVA Flowering Level
## Analysis of Variance Table
## 
## Response: F1$Chl5
##                   Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower.Level    3   1113  370.91  1.7103 0.1629
## Residuals       1786 387321  216.87

  • R.squared Flowering Level
## [1] 0.002864653
  • T.tests comparing Flowering Levels and Chlorophyll
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$Chl and FLWR1$Chl
## t = -0.86203, df = 18.114, p-value = 0.3999
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -3.262209  1.363413
## sample estimates:
##   mean of x   mean of y 
## -0.09097607  0.85842200
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$Chl and FLWR2$Chl
## t = -2.0943, df = 9.079, p-value = 0.06546
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -5.8214337  0.2205142
## sample estimates:
##   mean of x   mean of y 
## -0.09097607  2.70948366
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$Chl and FLWR3$Chl
## t = 0.83396, df = 10.12, p-value = 0.4236
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -1.928795  4.242233
## sample estimates:
##   mean of x   mean of y 
## -0.09097607 -1.24769509
## 
##  Welch Two Sample t-test
## 
## data:  FLWR1$Chl and FLWR2$Chl
## t = -1.1099, df = 17.858, p-value = 0.2818
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -5.356882  1.654759
## sample estimates:
## mean of x mean of y 
##  0.858422  2.709484
## 
##  Welch Two Sample t-test
## 
## data:  FLWR1$Chl and FLWR3$Chl
## t = 1.2331, df = 19.048, p-value = 0.2325
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -1.468068  5.680302
## sample estimates:
## mean of x mean of y 
##  0.858422 -1.247695
## 
##  Welch Two Sample t-test
## 
## data:  FLWR2$Chl and FLWR3$Chl
## t = 2.1175, df = 16.993, p-value = 0.04926
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  0.01431469 7.90004282
## sample estimates:
## mean of x mean of y 
##  2.709484 -1.247695
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing non-finite values (stat_summary).

  • ANOVA Flowering Presence
## Analysis of Variance Table
## 
## Response: F1$Chl5
##             Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower    1     39  39.177  0.1804 0.6711
## Residuals 1788 388395 217.223

  • R.squared Flowering Presence
## [1] 0.0001008579

Flavonol

## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing non-finite values (stat_summary).

  • ANOVA Flowering Levels
## Analysis of Variance Table
## 
## Response: F1$Flav5
##                   Df Sum Sq Mean Sq F value  Pr(>F)  
## F1$Flower.Level    3  0.590 0.19672  3.5826 0.01335 *
## Residuals       1786 98.069 0.05491                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared Flowering Levels
## [1] 0.00598177
  • T.tests comparing Flowering Levels and Flavonol
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$Flav and FLWR1$Flav
## t = -0.1909, df = 20.328, p-value = 0.8505
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.04941507  0.04112080
## sample estimates:
##     mean of x     mean of y 
## -0.0048934073 -0.0007462706
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$Flav and FLWR2$Flav
## t = -2.2842, df = 8.9901, p-value = 0.04826
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.1564348449 -0.0007465781
## sample estimates:
##    mean of x    mean of y 
## -0.004893407  0.073697304
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$Flav and FLWR3$Flav
## t = -0.58994, df = 9.9979, p-value = 0.5683
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.10199136  0.05929043
## sample estimates:
##    mean of x    mean of y 
## -0.004893407  0.016457057
## 
##  Welch Two Sample t-test
## 
## data:  FLWR1$Flav and FLWR2$Flav
## t = -1.9087, df = 13.878, p-value = 0.07721
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.158165728  0.009278579
## sample estimates:
##     mean of x     mean of y 
## -0.0007462706  0.0736973042
## 
##  Welch Two Sample t-test
## 
## data:  FLWR1$Flav and FLWR3$Flav
## t = -0.42387, df = 14.871, p-value = 0.6777
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.1037772  0.0693705
## sample estimates:
##     mean of x     mean of y 
## -0.0007462706  0.0164570573
## 
##  Welch Two Sample t-test
## 
## data:  FLWR2$Flav and FLWR3$Flav
## t = 1.1785, df = 17, p-value = 0.2548
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.04523505  0.15971554
## sample estimates:
##  mean of x  mean of y 
## 0.07369730 0.01645706
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing non-finite values (stat_summary).

  • ANOVA Flowering Presence
## Analysis of Variance Table
## 
## Response: F1$Flav5
##             Df Sum Sq  Mean Sq F value  Pr(>F)  
## F1$Flower    1  0.245 0.244694  4.4456 0.03513 *
## Residuals 1788 98.414 0.055042                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared Flowering Presence
## [1] 0.002480194

Height 2018

## Warning: Removed 89 rows containing non-finite values (stat_boxplot).
## Warning: Removed 89 rows containing non-finite values (stat_summary).

  • ANOVA Flowering Levels
## Analysis of Variance Table
## 
## Response: F1$H185
##                   Df Sum Sq Mean Sq F value    Pr(>F)    
## F1$Flower.Level    3  11639  3879.6  16.371 1.718e-10 ***
## Residuals       1718 407135   237.0                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared Flowering Levels
## [1] 0.02779275
  • T.tests comparing Flowering Levels and 2018 Height
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$H18 and FLWR1$H18
## t = -1.6305, df = 17.703, p-value = 0.1207
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -18.48037   2.34066
## sample estimates:
## mean of x mean of y 
## -2.410131  5.659726
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$H18 and FLWR2$H18
## t = -0.81929, df = 6.4906, p-value = 0.4417
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -22.95103  11.27931
## sample estimates:
## mean of x mean of y 
## -2.410131  3.425728
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$H18 and FLWR3$H18
## t = -1.5807, df = 9.3853, p-value = 0.147
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -19.310608   3.365938
## sample estimates:
## mean of x mean of y 
## -2.410131  5.562204
## 
##  Welch Two Sample t-test
## 
## data:  FLWR1$H18 and FLWR2$H18
## t = 0.26453, df = 11.816, p-value = 0.7959
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -16.19812  20.66612
## sample estimates:
## mean of x mean of y 
##  5.659726  3.425728
## 
##  Welch Two Sample t-test
## 
## data:  FLWR1$H18 and FLWR3$H18
## t = 0.014376, df = 20.604, p-value = 0.9887
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -14.02649  14.22153
## sample estimates:
## mean of x mean of y 
##  5.659726  5.562204
## 
##  Welch Two Sample t-test
## 
## data:  FLWR2$H18 and FLWR3$H18
## t = -0.25133, df = 11.217, p-value = 0.8061
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -20.80233  16.52937
## sample estimates:
## mean of x mean of y 
##  3.425728  5.562204
## Warning: Removed 89 rows containing non-finite values (stat_boxplot).
## Warning: Removed 89 rows containing non-finite values (stat_summary).

  • ANOVA Flower Presence
## Analysis of Variance Table
## 
## Response: F1$H185
##             Df Sum Sq Mean Sq F value   Pr(>F)   
## F1$Flower    1   2126 2125.89   8.776 0.003094 **
## Residuals 1720 416648  242.24                    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared Flower Presence
## [1] 0.005076449

Height 2019

## Warning: Removed 90 rows containing non-finite values (stat_boxplot).
## Warning: Removed 90 rows containing non-finite values (stat_summary).

  • ANOVA Flowering Level
## Analysis of Variance Table
## 
## Response: F1$H195
##                   Df Sum Sq Mean Sq F value    Pr(>F)    
## F1$Flower.Level    3   8766 2922.09  11.931 9.858e-08 ***
## Residuals       1717 420523  244.92                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared Flowering Level
## [1] 0.02042042
  • T.tests comparing Flowering Levels and 2019 Height
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$H19 and FLWR1$H19
## t = -1.7634, df = 18.363, p-value = 0.09447
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -17.725963   1.535942
## sample estimates:
## mean of x mean of y 
## -1.992529  6.102482
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$H19 and FLWR2$H19
## t = -0.12465, df = 6.2813, p-value = 0.9047
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -24.14341  21.77867
## sample estimates:
##  mean of x  mean of y 
## -1.9925285 -0.8101606
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$H19 and FLWR3$H19
## t = 0.3993, df = 9.2524, p-value = 0.6987
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -9.983022 14.284387
## sample estimates:
## mean of x mean of y 
## -1.992529 -4.143211
## 
##  Welch Two Sample t-test
## 
## data:  FLWR1$H19 and FLWR2$H19
## t = 0.66835, df = 8.7152, p-value = 0.5212
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -16.60158  30.42687
## sample estimates:
##  mean of x  mean of y 
##  6.1024818 -0.8101606
## 
##  Welch Two Sample t-test
## 
## data:  FLWR1$H19 and FLWR3$H19
## t = 1.5106, df = 18.391, p-value = 0.1479
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -3.982633 24.474019
## sample estimates:
## mean of x mean of y 
##  6.102482 -4.143211
## 
##  Welch Two Sample t-test
## 
## data:  FLWR2$H19 and FLWR3$H19
## t = 0.31093, df = 9.5696, p-value = 0.7625
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -20.69819  27.36429
## sample estimates:
##  mean of x  mean of y 
## -0.8101606 -4.1432112
## Warning: Removed 89 rows containing non-finite values (stat_boxplot).
## Warning: Removed 89 rows containing non-finite values (stat_summary).

  • ANOVA Flower Presence
## Analysis of Variance Table
## 
## Response: F1$H195
##             Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower    1    343  342.61   1.373 0.2415
## Residuals 1719 428947  249.53

  • R.squared Flower Presence
## [1] 0.0007980757

Height Difference 2018-2019

## Warning: Removed 90 rows containing non-finite values (stat_boxplot).
## Warning: Removed 90 rows containing non-finite values (stat_summary).

  • ANOVA Flowering Level
## Analysis of Variance Table
## 
## Response: F1$HD5
##                   Df Sum Sq Mean Sq F value    Pr(>F)    
## F1$Flower.Level    3  11642  3880.7  17.982 1.719e-11 ***
## Residuals       1717 370541   215.8                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared Flowering Level
## [1] 0.03046189
  • T.tests comparing Flowering Levels and 2018-19 Height Differences
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$HD5 and FLWR1$HD5
## t = 0.0726, df = 22.1, p-value = 0.9428
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -6.781665  7.273837
## sample estimates:
## mean of x mean of y 
## 0.6780263 0.4319402
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$HD5 and FLWR2$HD5
## t = 1.4803, df = 9.0022, p-value = 0.1729
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -2.604488 12.467963
## sample estimates:
##  mean of x  mean of y 
##  0.6780263 -4.2537116
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$HD5 and FLWR3$HD5
## t = 2.0307, df = 9.4119, p-value = 0.07149
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -1.10757 21.88518
## sample estimates:
##  mean of x  mean of y 
##  0.6780263 -9.7107801
## 
##  Welch Two Sample t-test
## 
## data:  FLWR1$HD5 and FLWR2$HD5
## t = 1.0896, df = 17.451, p-value = 0.2907
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -4.369425 13.740729
## sample estimates:
##  mean of x  mean of y 
##  0.4319402 -4.2537116
## 
##  Welch Two Sample t-test
## 
## data:  FLWR1$HD5 and FLWR3$HD5
## t = 1.7507, df = 14.317, p-value = 0.1014
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -2.257682 22.543123
## sample estimates:
##  mean of x  mean of y 
##  0.4319402 -9.7107801
## 
##  Welch Two Sample t-test
## 
## data:  FLWR2$HD5 and FLWR3$HD5
## t = 0.94742, df = 12.738, p-value = 0.3611
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -7.012502 17.926639
## sample estimates:
## mean of x mean of y 
## -4.253712 -9.710780
## Warning: Removed 90 rows containing non-finite values (stat_boxplot).
## Warning: Removed 90 rows containing non-finite values (stat_summary).

  • ANOVA Flowering Presence
## Analysis of Variance Table
## 
## Response: F1$HD5
##             Df Sum Sq Mean Sq F value    Pr(>F)    
## F1$Flower    1   4205  4205.2  19.125 1.298e-05 ***
## Residuals 1719 377978   219.9                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared Flowering Presence
## [1] 0.01100306

Measure Correlations

Plots

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 21 rows containing non-finite values (stat_smooth).

## Warning: Removed 21 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 110 rows containing non-finite values (stat_smooth).
## Warning: Removed 110 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 110 rows containing non-finite values (stat_smooth).

## Warning: Removed 110 rows containing missing values (geom_point).

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 110 rows containing non-finite values (stat_smooth).

## Warning: Removed 110 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 110 rows containing non-finite values (stat_smooth).
## Warning: Removed 110 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 110 rows containing non-finite values (stat_smooth).

## Warning: Removed 110 rows containing missing values (geom_point).

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 110 rows containing non-finite values (stat_smooth).

## Warning: Removed 110 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 110 rows containing non-finite values (stat_smooth).

## Warning: Removed 110 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 110 rows containing non-finite values (stat_smooth).

## Warning: Removed 110 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 110 rows containing non-finite values (stat_smooth).

## Warning: Removed 110 rows containing missing values (geom_point).

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 90 rows containing non-finite values (stat_smooth).
## Warning: Removed 90 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 90 rows containing non-finite values (stat_smooth).

## Warning: Removed 90 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 90 rows containing non-finite values (stat_smooth).

## Warning: Removed 90 rows containing missing values (geom_point).

### Anthocyanin and Chlorophyll

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Anth5
##             Df  Sum Sq  Mean Sq F value    Pr(>F)    
## F1$Chl5      1 0.31585 0.315847  207.87 < 2.2e-16 ***
## Residuals 1788 2.71674 0.001519                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared
## [1] 0.104151

Anthocyanin and Flavonol

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Anth5
##             Df  Sum Sq  Mean Sq F value    Pr(>F)    
## F1$Flav5     1 0.09389 0.093889  57.125 6.493e-14 ***
## Residuals 1788 2.93870 0.001644                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared
## [1] 0.03096008

Anothcyanin and Height 2018

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Anth5
##             Df  Sum Sq   Mean Sq F value Pr(>F)
## F1$H185      1 0.00124 0.0012373  0.7231 0.3953
## Residuals 1699 2.90726 0.0017112

  • R.squared
## [1] 0.0004254108

Anthocyanin and Height 2019

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Anth5
##             Df  Sum Sq    Mean Sq F value Pr(>F)
## F1$H195      1 0.00004 0.00004488  0.0262 0.8714
## Residuals 1699 2.90846 0.00171186

  • R.squared
## [1] 1.54299e-05

Anthocyanin and Height Difference Between 2018 and 2019

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Anth5
##             Df  Sum Sq   Mean Sq F value Pr(>F)
## F1$HD5       1 0.00193 0.0019302  1.1283 0.2883
## Residuals 1699 2.90657 0.0017108

  • R.squared
## [1] 0.0006636417

Chlorophyll and Flavonol

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Anth5
##             Df  Sum Sq  Mean Sq F value    Pr(>F)    
## F1$Flav5     1 0.09389 0.093889  57.125 6.493e-14 ***
## Residuals 1788 2.93870 0.001644                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared
## [1] 0.03096008

Chlorophyll and Height 2018

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Chl5
##             Df Sum Sq Mean Sq F value Pr(>F)
## F1$H185      1    443  443.05  2.0322 0.1542
## Residuals 1699 370412  218.02

  • R.squared
## [1] 0.001194672

Chlorophyll and Height 2019

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Chl5
##             Df Sum Sq Mean Sq F value Pr(>F)
## F1$H195      1     57  56.603  0.2594 0.6106
## Residuals 1699 370798 218.245

  • R.squared
## [1] 0.0001526278

Chlorophyll and Height Difference Between 2018 and 2019

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Chl5
##             Df Sum Sq Mean Sq F value Pr(>F)
## F1$HD5       1    197  196.57   0.901 0.3426
## Residuals 1699 370658  218.16

  • R.squared
## [1] 0.0005300545

Flavonol and Height 2018

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Flav5
##             Df Sum Sq  Mean Sq F value Pr(>F)
## F1$H185      1  0.076 0.076208  1.3799 0.2403
## Residuals 1699 93.832 0.055228

  • R.squared
## [1] 0.0008115148

Flavonol and Height 2019

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Flav5
##             Df Sum Sq  Mean Sq F value  Pr(>F)  
## F1$H195      1  0.201 0.201298  3.6497 0.05625 .
## Residuals 1699 93.707 0.055154                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared
## [1] 0.002143548

Flavonol and Height Difference Between 2018 and 2019

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Flav5
##             Df Sum Sq Mean Sq F value   Pr(>F)   
## F1$HD5       1  0.584 0.58427  10.637 0.001131 **
## Residuals 1699 93.324 0.05493                    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared
## [1] 0.006221659

Height 2018 and 2019

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$H185
##             Df Sum Sq Mean Sq F value    Pr(>F)    
## F1$H195      1 125710  125710  740.77 < 2.2e-16 ***
## Residuals 1719 291720     170                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared
## [1] 0.3011528

Height 2018 and Height Difference Between 2018 and 2019

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$H185
##             Df Sum Sq Mean Sq F value    Pr(>F)    
## F1$HD5       1  89593   89593  469.78 < 2.2e-16 ***
## Residuals 1719 327837     191                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared
## [1] 0.2146297

Height 2019 and Height Difference Between 2018 and 2019

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$H195
##             Df Sum Sq Mean Sq F value    Pr(>F)    
## F1$HD5       1 101633  101633   533.2 < 2.2e-16 ***
## Residuals 1719 327656     191                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared
## [1] 0.2146297